***** To join INSNA, visit http://www.insna.org ***** Dear all,
I would very much appreciate it if you could spread the word and/or circulate this info among students interested in Complex Systems and Networks.
Many thanks and best wishes,
Lucas Lacasa

SHORT DESCRIPTION:
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MSc Network Science, run jointly by the School of Mathematical Sciences and the School of Electronic Engineering and Computer Science at the Russell's Group  
Queen Mary University of London is now accepting applications for the 2016/2017 entry. This is a specialist masters in network science and mathematical modelling of complex systems, along with the principal analytical, numerical and data analysis methodologies. This MSc will open to students a host of career opportunities in modelling of complex systems, networks and data science related industries that require such specialist knowledge and skills. Internship possibilities available in a selection of world leading companies in London and Paris, as well as PhD opportunities in the complex systems & networks group.

More information at http://www.maths.qmul.ac.uk/prospective-students/msc-mathematics-networks
Apply online http://www.qmul.ac.uk/postgraduate/taught/coursefinder/courses/143463.html


LONG DESCRIPTION:
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Our MSc Network Science, run jointly by the School of Mathematical Sciences and the School of Electronic Engineering and Computer Science at the Russell's Group  
Queen Mary University of London is now accepting applications for the 2016/2017 entry.
 

What do Facebook, the financial system, Internet or the brain have in common? 
"Everything is connected, all is network"

From the underlying skeleton of social relations, the interdependent evolution of our financial system, to the emergent collective computation in the brain, most of the complex systems that appear in society, technology, and nature are ultimately characterised by a nontrivial pattern of inter-relations. This underlying architecture is in turn shaping how information diffuses and spreads, how resilient the system is against attacks or perturbations, or how complex patterns emerge at the systemic level from the aggregation of seemingly simple individuals. Network Science is a very active and rapidly evolving research field with high societal impact, which stands at the crossroads of graph theory, complexity science and data analysis. Addressing the description and modelling of the architecture and dynamics of complex systems -systems composed by many interacting units that show collective behaviour- it stands as a new kind of science to cope with some of the most challenging endeavours we face today, in an ever increasingly more connected society. Its impact and applications outside academia pervades technological sectors such as communications and infrastructures (Internet, transportation networks, energy networks, urban mobility), finance (financial risk and systemic instability, financial networks, interbank cross-correlations), marketing and IT (social media, data analytics), public health (epidemic spreading models), or biostatistics and network biology (brain modelling, protein interaction networks, postgenomic era), to cite a few. 

Aims and list of main topics
This MSc is aimed towards students with a mathematical background who wish to enter a career involving analysis and optimisation of diverse kinds of networks, networked dynamics and models. We welcome applications from highly motivated top students around the world with keen and genuine interest in interdisciplinary science that have received some mathematical training in their undergraduate studies, such as BSc in Mathematics, Physics, Computer Science, Statistics, Economics, Engineering...
Students will be able to choose a tailored curriculum with topics such as Graphs and Networks,Machine Learning, Research Methods, Data Mining, Topics in Scientific Computing, Complex Systems, Processes on Networks, Digital Media and Social Networks, Computational statistics,Financial programming or Database systems.
All students will make a research project supervised by world leading experts in Network Science including Prof. Vito Latora, Dr. Ginestra Bianconi or Dr. Vincenzo Nicosia, and will be able to interact with PhD students in Network Science as well as attend extra-curricular events organised with our industrial stakeholders.

The best place to study networks and complex systems
This is a pioneering MSc in the UK, a joint programme, taught by our Schools of Mathematical Sciences, and Electronic Engineering and Computer Science, drawing on their strengths in research and teaching in the area of complex networks, mathematical modelling of complex systems, and data mining.
We teach what we know and what we do best. Within the School of Mathematics, the Complex Systems & Networks group is one of the biggest hubs in Network Science within the UK, where we address both fundamental and applied challenges in the mathematical modelling of complex systems with clear societal impact, in collaboration with several industrial stakeholders. Within the School of Electronic Engineering, the Networks group was founded in 1987, and has hugely expanded ever since, bringing their expertise in online social networks, data mining and cloud computing. This group is internationally recognised for their pioneering and ground-breaking research in several areas including machine learning and applied network analysis. This expertise uniquely complements the more theoretical knowledge offered by the School of Mathematical Sciences, providing a well balanced mix of theory and applications and offering a deep and robust programme that combines the foundations of the mathematics of networks with the latest cutting edge applications in real world problems including modelling and data analytics. The coalescence of both groups expertises has fostered the creation of this unique MSc.

Queen Mary is a member of the prestigious Russell Group of leading UK universities, combining world-class research, teaching excellence and unrivalled links with business and the public sector. We are one of the UKs leading universities in the most recent national assessment of research quality, we were placed ninth in the UK (REF 2014) amongst multi-faculty universities.

Potential job opportunities
This unique MSc will open to students a host of career opportunities in modelling of complex systems, networks and data science related industries that require such specialist knowledge and skills, spanning the IT, financial, and biomedical sectors. It has been recognised as a groundbreaking MSc by Networking+ magazine and indeed this MSc is currently sponsored by Neo4J who offers each year two Neo4J prizes to the best MSc Network Science student and dissertation. Last year winner for the best student award (Helena Andres Terre) is now doing a PhD at the University of Cambridge, whereas the winner for the best dissertation (Brad Hunn) is working as a contractor.
Additionally, each year we give our graduates internship possibilities at leading companies, including Neo Technology (London, UK), Telefonica Research Labs (Barcelona, Spain) or Hopital de la Salpetriere (Paris, France). We also offer PhD opportunities in the complex systems & networks group. as well as research collaborations with other groups in the UK and around the globe.


More information at http://www.maths.qmul.ac.uk/prospective-students/msc-mathematics-networks
Apply online http://www.qmul.ac.uk/postgraduate/taught/coursefinder/courses/143463.html
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Dr. Lucas Lacasa
Lecturer in Applied Mathematics
Queen Mary University of London






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